--- name: tonone-onboard description: 'First-run onboarding — detect what kind of project this is, recommend a four-agent roster instead of all 100, and print the one-line install command. Use when asked "how do I use tonone", "which agents do I need", "what can tonone do", "show me around", or "first steps".' allowed-tools: Bash, Read, AskUserQuestion version: 0.9.0 author: tonone-ai license: MIT compatibility: Designed for Claude Code tags: [onboarding, getting-started, roster, recommendation] --- # tonone-onboard Cross-agent onboarding. Not tied to a single agent. The default install registers every agent in every session. That is the wrong default for almost every repository: most projects need four or five specialists, and Apex reaches the rest on demand. This skill proposes the roster that fits **this** repository and hands it to `/apex-profile` to write. Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose. This skill should land in roughly a dozen lines. An onboarding message that scrolls is an onboarding message nobody reads. Always runs. Never checks the marker file — replay it as often as you like. To re-show the SessionStart install banner, delete `~/.config/tonone/onboarded`. ## Steps ### Step 1: Detect the project shape Run the shared detector. It is the same signal gathering and scoring the SessionStart banner and the skill gate use, so all three agree by construction. `CLAUDE_PLUGIN_ROOT` is **not** exported into the Bash tool's environment, so the detector has to be located before it can be run. Paste this block verbatim — it checks the plugin root when one is set, the repository checkout you are standing in, then the installed plugin cache: ```bash shape="" for c in "${CLAUDE_PLUGIN_ROOT:-/nonexistent}/lib/signals/project-shape.js" \ "${CLAUDE_PLUGIN_ROOT:-/nonexistent}/../../lib/signals/project-shape.js" \ "$PWD/lib/signals/project-shape.js"; do [ -f "$c" ] && shape="$c" && break done if [ -z "$shape" ]; then found=$(find "$HOME/.claude/plugins/cache" -maxdepth 6 \ -path "*/lib/signals/project-shape.js" 2>/dev/null | head -1) [ -n "$found" ] && shape="$found" fi if [ -n "$shape" ]; then node "$shape" --pretty --cwd "$PWD" else echo '{"ok":false,"error":"detector not on disk","source":"default"}' fi ``` Written this way the block exits 0 and prints one JSON object on every path, under bash, zsh and sh alike. The detector's own CLI never exits non-zero either; the `else` branch covers the one case it cannot, which is not being installed at all. Read `ok` first — a `false` there means no detection happened, so do not present the roster in it as a match. The JSON object: | Field | Use | | -------------- | --------------------------------------------------------------------- | | `label`, `why` | What it decided, and the one-line reason | | `agents` | The recommended roster, Apex always first | | `bundles` | Wider bundles in the same domain — a superset, never the roster | | `commands` | `commands[0]` installs exactly the roster; the rest are bundles | | `evidence` | The files and dependencies that drove the match | | `source` | `signals` deterministic, `jev`/`local` tie-broken, `default` no match | | `alternate` | The runner-up roster, or `null` | Do not re-derive any of this by hand and do not substitute your own roster. If `ok` is `false` — the detector is not on disk, which happens when only a single agent plugin is installed rather than the bundle — say so in one line and hand off to `/apex-profile` with its **Preset** option, letting its curated preset table pick the roster. Do not fall back to the full 100-agent team: an undetected project is the case this skill exists for, not an exception to it. ### Step 2: Present the recommendation One box, under 12 lines. Report `source` honestly — a `default` result means nothing matched, not that the starter roster is right: ``` ┌────────────────────────────────────────────────────────┐ │ tonone — recommended roster │ ├────────────────────────────────────────────────────────┤ │ Detected Frontend web app │ │ Evidence next, next.config.js, react │ │ Roster apex, prism, form, draft, axe │ │ Why UI work, a design system, an a11y pass │ └────────────────────────────────────────────────────────┘ claude plugin install apex@tonone-ai prism@tonone-ai form@tonone-ai \ draft@tonone-ai axe@tonone-ai ``` Print `commands[0]` verbatim, below the box where it has room to wrap. Never print a bundle command in its place: `design-team` installs ten design agents and still misses Prism, so it is not the roster the box just promised. Add one line only when it earns its place: - `source` is `default` — ● INFO No strong signal; this is the generic starter roster. - `alternate` is set — ● INFO Runner-up: ``. Say `both` to install it too. - `bundles` is non-empty — ● INFO Whole discipline instead: `commands[1]`. ### Step 3: Confirm (AskUserQuestion, single-select) - **Install this roster** — the recommended agents, nothing else - **Roster plus the runner-up** — offer only when `alternate` is set - **Full team** — all 100 agents, the current default - **Just show me around** — skip installation, go to Step 5 ### Step 4: Hand off to apex-profile `/apex-profile` owns agent roster configuration — it writes `enabledPlugins` into `.claude/settings.json` or `.claude/settings.local.json`, merging rather than overwriting, and it asks which of the two. Do not write either file here. Invoke `/apex-profile` with the **Custom list** option and the `agents` array from Step 1 as the list. This skill is the recommender; apex-profile is the writer. If the user wants a different set, let apex-profile's own preset table take over — do not negotiate the roster twice. State plainly that plugin enablement is read at startup, so the change takes effect in the **next** Claude Code session. ### Step 5: Orientation (only if asked) Keep it to this block. The full agent table lives in `CLAUDE.md` and `docs/agent-index.json`; do not reproduce 100 rows in the terminal. ``` /apex-takeover hand any task to the team — Apex routes it /apex-route reach a specialist outside your roster, on demand /apex-profile change the installed roster later /atlas-onboard generate onboarding docs for this project ``` Mental model, in three lines: - You talk to Apex. Apex picks the specialist. You never dispatch by name. - A roster is what is installed. `/apex-route` still reaches all 100. - Each session gets its own git worktree branch, so parallel sessions never collide, and a session that changed nothing removes its branch on close. ## Key Rules - **Recommend, never install silently.** No plugin is installed and no settings file is written without an explicit confirmation in Step 3. - **apex-profile writes the config.** This skill detects and proposes. Writing `enabledPlugins` in two places would produce two sources of truth. - **Never invent a roster or a bundle.** Use exactly what the detector returns; its bundles are checked against `bundle/` by `tests/test_project_shape.js`. - **Report the source.** `signals` is deterministic evidence. `local` is lexical overlap from the key-free scorer, not judgement. `default` means no match. - **No credentials, ever.** The detector needs no key and no network. Never suggest setting one to improve the recommendation. - **Stay short.** Steps 1-4 produce one box plus at most two extra lines. - **Do not list all 100 agents.** That is the problem this skill exists to fix. ## Output Format One box (the Step 2 skeleton), then the confirmation question, then a single closing line naming what was written and when it takes effect: ``` Roster written to .claude/settings.local.json — active next session. ``` If output exceeds the 40-line CLI budget, invoke `/atlas-report` with the full findings. The HTML report is the output; the CLI is the receipt — box header, one-line verdict, and the report path. --- Source attribution: tonone-ai Original project: https://github.com/tonone-ai/tonone/blob/1ceec80367a4e846e2f209cc87eea9d7544bd978/skills/tonone-onboard/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Dave AI. ## Upstream license notice MIT License Copyright (c) 2026 tonone-ai Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Dave AI resource metadata Creator / publisher: tonone-ai Original project: https://github.com/tonone-ai/tonone/blob/1ceec80367a4e846e2f209cc87eea9d7544bd978/skills/tonone-onboard/SKILL.md Attribution basis: Source repository record Fields of work: Design, Marketing, Product Management, Sales, Customer Support Roles: Customer Success Manager, Growth Marketer, Product Manager, Technical Support, UX Designer Specialties: Specialty not specified Tools: Tonone Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: c5a10d6a5a30aa82f9060e92ceeca91b3dfa903c733211a6ebe7f5eefcce476a